• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Ear Recognition by Major Axis and Complex Vector Manipulation

Vol. 11, No. 3, March 30, 2017
10.3837/tiis.2017.03.022, Download Paper (Free):

Abstract

In this study, each pixel in an ear is used as a centroid to generate a cake. Subsequently the major axis length of this cake is computed and obtained. This obtained major axis length serves as a feature to recognize an ear. Later, the ear hole is used as a centroid and a 16-circle template is generated to extract the major axis lengths of the ear. The 16-circle template extracted signals are used to recognize an ear. In the next step, a ring-to-line mapping technique is used to map these major axis lengths to several straight-line signals. Next, the complex plane vector computing technique is used to determine the similarity of these major axis lengths, whereby a solution to the image-rotating problem is achieved. The aforementioned extracted signals are also compared to the ones that are extracted from its neighboring pixels, whereby solving the image-shifting problem. The algorithm developed in this study can precisely identify an ear image by solving the image rotation and image shifting problems.


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Cite this article

[IEEE Style]
C. Su, "Ear Recognition by Major Axis and Complex Vector Manipulation," KSII Transactions on Internet and Information Systems, vol. 11, no. 3, pp. 1650-1669, 2017. DOI: 10.3837/tiis.2017.03.022.

[ACM Style]
Ching-Liang Su. 2017. Ear Recognition by Major Axis and Complex Vector Manipulation. KSII Transactions on Internet and Information Systems, 11, 3, (2017), 1650-1669. DOI: 10.3837/tiis.2017.03.022.

[BibTeX Style]
@article{tiis:21405, title="Ear Recognition by Major Axis and Complex Vector Manipulation", author="Ching-Liang Su and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2017.03.022}, volume={11}, number={3}, year="2017", month={March}, pages={1650-1669}}